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          catfish
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                <div class="bbp-reply-header" id="post-412999">
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                   2015年11月11日 下午2:36
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/412994/">
                    ggplot和plot作的图能进行组合么？
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                   回复
                   <a href="http://cos.name/cn/topic/412994/#post-412997" rel="nofollow">
                    2 楼
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                   的
                   <a href="http://cos.name/cn/profile/81532/" rel="nofollow">
                    Ihavenothing
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                   ：
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                  <p>
                   恩，找到了。http://stackoverflow.com/questions/13021863/plots-generated-by-plot-and-ggplot-side-by-side
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                   2014年2月21日 上午4:33
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/151007/">
                    数据框嵌套数据框
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                   2 楼
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                  <p>
                   回复 第1楼 的 catfish：解嵌套的方法很简单：
                  </p>
                  <pre class="highlight ">&gt; df=as.data.frame(as.list(df))
&gt; str(df)
'data.frame':	3 obs. of  3 variables:
 $ ID   : int  11 12 13
 $ FOO.a: chr  "a" "b" "x"
 $ FOO.b: chr  "b" "c" "y"
&gt; df
  ID FOO.a FOO.b
1 11     a     b
2 12     b     c
3 13     x     y
</pre>
                  <p>
                   不过数据框的嵌套是怎么构造的还是不明白。
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                   2013年6月10日 上午8:55
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/110745/">
                    knitr输出结果过长
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                   3 楼
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                   回复 第2楼 的 daigazi：恩，这种方式很实用，但是需要额外的插入一些换行符，如果重新设置页边距，可能这些换行符的位置也需要改变。所以，我想问的是可否通过设置什么参数能够让其自动根据textwidth换行。
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                   2013年5月25日 上午11:21
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/110508/">
                    Rstudio在ubuntu10.04中中文支持的问题
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                   回复 第3楼 的 肖楠：果然是缺乏字体，装了微米黑，正黑后问题就o了。其实也想升级系统来着，不过装了13.04虚拟机跑不动了，无奈退回到10.04，不过设置起来还是蛮麻烦的。再次拜谢肖楠大神。[s:11]
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                   2013年2月6日 上午4:17
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/109214/">
                    WinBUGS问题求解
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                   9 楼
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                   回复 第7楼 的 enita：我没有太明白你问题的意思。就我给出的这个代码而言，主要是针对做二分类变量Logistic回归时会存在协变量部分缺失，然后假定协变量都是连续的且服从多元正态分布，这样可以通过Bayesian方法来估计含有缺失数值的模型参数值以及缺失数值的期望与方差。问题就在于目前版本的OpenBUGS不能很好的解决含有缺失值的多元正态协变量的参数估值。这点在WinBUGS1.4中没有问题。如果你单纯地想知道怎么用R来调用BUGS代码的话，可以读一下R2WinBUGS或者R2OpenBUGS中bugs函数的帮助问题，特别是example中的例子。
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                   2013年2月6日 上午4:05
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                    WinBUGS问题求解
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                   8 楼
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                   回复 第6楼 的 YSU：恩，在WinBUGS1.4中运行没有错误，但在OpenBUGS中确实存在存在问题。我已经联系过OpenBUGS的作者，他对源代码作了一点小改动，估计下一个版本就不会有问题了。
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                   2013年1月26日 上午2:52
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                    WinBUGS问题求解
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                   catfish
                  </a>
                  <br/>
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                   普通会员
                  </div>
                 </div>
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                 <div class="bbp-reply-content">
                  <p>
                   回复 第4楼 的 YSU：谢谢你的答复，我只是想测试一下代码有没有问题，所以简单处理了一下。原来的代码跟你现在发的差不多。不过，我用你的代码编译还是不成功。我用的是OpenBUGS 3.2.2 rev1063 (2012-7-15)版本的，难道是有bug？
                  </p>
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                <div class="bbp-reply-header" id="post-342023">
                 <div class="bbp-meta">
                  <span class="bbp-reply-post-date">
                   2013年1月25日 上午11:25
                  </span>
                  <span class="bbp-header">
                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/109214/">
                    WinBUGS问题求解
                   </a>
                  </span>
                  <a class="bbp-reply-permalink" href="http://cos.name/cn/topic/109214/#post-342023">
                   3 楼
                  </a>
                  <span class="bbp-admin-links">
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                 <div class="bbp-reply-author">
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                   <img src="http://sdn.geekzu.org/avatar/05e4057d68060ece41c68f31982004eb?s=80&amp;d=monsterid&amp;r=g"/>
                  </a>
                  <br/>
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                   catfish
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                   普通会员
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                  <p>
                   以下情况也可以运行：
                  </p>
                  <p>
                   模型如下：
                  </p>
                  <pre class="highlight ">    model
    {
        for (i in 1:n) {
            y[i] ~ dbern(p[i])
            logit(p[i]) &lt;- b[1] + b[2] * x[i, 1] + b[3] * x[i, 2]
            x[i, 1] ~ dnorm(mu, tau.m)
            x[i, 2] ~ dnorm(mu, tau.m)
        }
        for (i in 1:3) {
            b[i] ~ dnorm(0.00000E+00, 1.00000E-04)
        }
        mu ~ dnorm(0.00000E+00, 1.00000E-04)
        tau.m ~ dgamma(1.00000E-04, 1.00000E-04)
    }
</pre>
                  <p>
                  </p>
                  <p>
                   数据如下：
                  </p>
                  <pre>    list(n=5.00000E+01, y=c(0.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00), x= structure(.Data= c(-5.60476E-01,     NA, -2.30177E-01, -2.85468E-02,     NA, -4.28705E-02, 7.05084E-02, 1.36860E+00, 1.29288E-01, -2.25771E-01, 1.71506E+00, 1.51647E+00,     NA, -1.54875E+00,     NA, 5.84614E-01,     NA, 1.23854E-01, -4.45662E-01,     NA,     NA, 3.79639E-01, 3.59814E-01, -5.02323E-01, 4.00771E-01,     NA, 1.10683E-01,     NA, -5.55841E-01, -1.07179E+00, 1.78691E+00, 3.03529E-01, 4.97850E-01,     NA,     NA,     NA, 7.01356E-01, 9.22267E-01, -4.72791E-01, 2.05008E+00, -1.06782E+00,     NA,     NA, -2.30917E+00,     NA, 1.00574E+00,     NA,     NA, -6.25039E-01, -6.88009E-01, -1.68669E+00, 1.02557E+00, 8.37787E-01,     NA,     NA, -1.22072E+00, -1.13814E+00, 1.81303E-01, 1.25381E+00,     NA, 4.26464E-01,     NA, -2.95071E-01, 3.85280E-01, 8.95126E-01, -3.70660E-01, 8.78133E-01, 6.44377E-01, 8.21581E-01, -2.20487E-01, 6.88640E-01, 3.31782E-01, 5.53918E-01,     NA, -6.19117E-02, 4.35181E-01, -3.05963E-01, -3.25932E-01, -3.80471E-01, 1.14881E+00,     NA, 9.93504E-01,     NA, 5.48397E-01,     NA, 2.38732E-01,     NA,     NA, 1.20796E+00, 1.36065E+00, -1.12311E+00, -6.00260E-01,     NA, 2.18733E+00,     NA, 1.53261E+00, 7.79965E-01,     NA,     NA, -1.02642E+00), .Dim=c(50, 2)))
</pre>
                  <p>
                  </p>
                  <p>
                   初值如下：
                  </p>
                  <pre>    list(mu=0.00000E+00, tau.m=1.00000E-01, b=c(0.00000E+00, 1.00000E+00, 1.00000E+00), x= structure(.Data= c(    NA, 0.00000E+00,     NA,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA, 0.00000E+00,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA), .Dim=c(50, 2)))
</pre>
                  <p>
                  </p>
                  <p>
                   这个时候协变量x1和x2是独立的先验。
                  </p>
                  <p>
                   ============================
                  </p>
                  <p>
                   对于连续的响应变量，也没有问题。
                  </p>
                  <p>
                   模型如下：
                  </p>
                  <pre class="highlight ">    model
    {
        for (i in 1:n) {
            y[i] ~ dlnorm(u[i], tau.u)
            u[i] &lt;- b[1] + b[2] * x[i, 1] + b[3] * x[i, 2]
            x[i, 1:2] ~ dmnorm(m[], tau.m[, ])
        }
        for (i in 1:3) {
            b[i] ~ dnorm(0.00000E+00, 1.00000E-04)
        }
        tau.u ~ dgamma(0.01, 0.01)
        m[1] &lt;- 0.00000E+00
        m[2] &lt;- 0.00000E+00
        tau.m[1:2, 1:2] ~ dwish(t.m[, ], 2)
        t.m[1, 1] &lt;- 1.00000E-04
        t.m[1, 2] &lt;- 0.00000E+00
        t.m[2, 1] &lt;- 0.00000E+00
        t.m[2, 2] &lt;- 1.00000E-04
    }
</pre>
                  <p>
                  </p>
                  <p>
                   数据如下：
                  </p>
                  <pre>    list(n=5.00000E+01, y=c(8.65414E-01, 1.12487E+00, 5.24423E+00, 2.81524E+00, 1.17452E+00, 1.72255E+01, 8.21693E-01, 5.21954E-01, 8.12168E-01, 1.12307E+00, 5.43900E+00, 1.29219E+00, 1.55146E+00, 8.78418E-01, 3.83364E-01, 7.27281E+00, 2.61510E+00, 2.17445E-01, 4.72890E+00, 2.88193E+00, 3.49869E-01, 2.72516E-01, 1.04425E+00, 4.36516E-01, 4.26072E-01, 4.36151E-01, 2.59282E+00, 6.89375E-01, 5.29516E-01, 4.39433E+00, 2.26427E+00, 1.22845E+00, 2.31174E+00, 4.35802E+00, 1.91039E+00, 2.72710E+00, 4.45600E+00, 1.54100E+00, 8.07743E-01, 1.57474E+00, 1.09645E+00, 1.40779E+00, 4.02234E-01, 7.33391E+00, 8.09886E+00, 3.37779E-01, 3.51361E+00, 1.79529E+00, 2.53790E+00, 4.99779E-01), x= structure(.Data= c(    NA, 2.53319E-01, -2.30177E-01, -2.85468E-02, 1.55871E+00,     NA, 7.05084E-02, 1.36860E+00, 1.29288E-01, -2.25771E-01, 1.71506E+00, 1.51647E+00, 4.60916E-01,     NA, -1.26506E+00, 5.84614E-01, -6.86853E-01, 1.23854E-01,     NA,     NA, 1.22408E+00, 3.79639E-01, 3.59814E-01, -5.02323E-01,     NA,     NA,     NA, -1.01858E+00, -5.55841E-01, -1.07179E+00, 1.78691E+00, 3.03529E-01,     NA, 4.48210E-01,     NA, 5.30042E-02, 7.01356E-01, 9.22267E-01, -4.72791E-01,     NA,     NA, -4.91031E-01, -2.17975E-01, -2.30917E+00, -1.02600E+00,     NA,     NA,     NA, -6.25039E-01, -6.88009E-01, -1.68669E+00, 1.02557E+00,     NA,     NA, 1.53373E-01, -1.22072E+00, -1.13814E+00,     NA,     NA, -1.38891E-01,     NA,     NA, -2.95071E-01, 3.85280E-01, 8.95126E-01,     NA, 8.78133E-01, 6.44377E-01, 8.21581E-01, -2.20487E-01, 6.88640E-01, 3.31782E-01,     NA, 1.09684E+00, -6.19117E-02,     NA, -3.05963E-01, -3.25932E-01, -3.80471E-01,     NA, -6.94707E-01,     NA, -2.07917E-01, 5.48397E-01, -1.26540E+00, 2.38732E-01,     NA, -6.27906E-01, 1.20796E+00, 1.36065E+00, -1.12311E+00, -6.00260E-01, -4.02885E-01,     NA, -4.66655E-01,     NA,     NA, -2.35700E-01, -8.33691E-02,     NA), .Dim=c(50, 2)))
</pre>
                  <p>
                  </p>
                  <p>
                   初值如下：
                  </p>
                  <pre>    list(b=c(0.00000E+00, 1.00000E+00, 1.00000E+00), tau.m= structure(.Data= c(1.00000E-01, 0.00000E+00, 0.00000E+00, 1.00000E-01), .Dim=c(2, 2)), tau.u=1.00000E-01, x= structure(.Data= c(0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA,     NA,     NA, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA,     NA, 0.00000E+00,     NA,     NA, 0.00000E+00,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA, 0.00000E+00), .Dim=c(50, 2)))
</pre>
                  <p>
                  </p>
                  <p>
                   不知是什么原因？
                  </p>
                 </div>
                 <!-- .bbp-reply-content -->
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                <!-- .reply -->
                <div class="bbp-reply-header" id="post-341987">
                 <div class="bbp-meta">
                  <span class="bbp-reply-post-date">
                   2013年1月25日 上午2:12
                  </span>
                  <span class="bbp-header">
                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/109214/">
                    WinBUGS问题求解
                   </a>
                  </span>
                  <a class="bbp-reply-permalink" href="http://cos.name/cn/topic/109214/#post-341987">
                   2 楼
                  </a>
                  <span class="bbp-admin-links">
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                   catfish
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                   普通会员
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                 <div class="bbp-reply-content">
                  <p>
                   另外，同样的方式，对于1个协变量的情况，则一点儿问题都没有，例如
                  </p>
                  <pre class="highlight ">    model
    {
        for (i in 1:n) {
            y[i] ~ dbern(p[i])
            logit(p[i]) &lt;- b0 + b1 * x[i]
            x[i] ~ dnorm(mu, tau.m)
        }
        mu ~ dnorm(0.00000E+00, 1.00000E-04)
        tau.m ~ dgamma(1.00000E-04, 1.00000E-04)
        b0 ~ dnorm(0.00000E+00, 1.00000E-04)
        b1 ~ dnorm(0.00000E+00, 1.00000E-04)
    }
</pre>
                  <p>
                  </p>
                  <p>
                   数据如下：
                  </p>
                  <pre>    list(n=5.00000E+01, y=c(1.00000E+00, 0.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, 1.00000E+00), x=c(-5.60476E-01, -2.30177E-01, 1.55871E+00, 7.05084E-02, 1.29288E-01, 1.71506E+00, 4.60916E-01, -1.26506E+00, -6.86853E-01, -4.45662E-01, 1.22408E+00, 3.59814E-01, 4.00771E-01, 1.10683E-01,     NA, 1.78691E+00, 4.97850E-01, -1.96662E+00, 7.01356E-01, -4.72791E-01,     NA,     NA, -1.02600E+00, -7.28891E-01, -6.25039E-01, -1.68669E+00,     NA, 1.53373E-01,     NA, 1.25381E+00,     NA, -2.95071E-01, 8.95126E-01, 8.78133E-01, 8.21581E-01, 6.88640E-01,     NA,     NA, -3.05963E-01, -3.80471E-01,     NA, -2.07917E-01,     NA, 2.16896E+00, 1.20796E+00, -1.12311E+00, -4.02885E-01, -4.66655E-01, 7.79965E-01,     NA))
</pre>
                  <p>
                  </p>
                  <p>
                   初始值如下：
                  </p>
                  <pre>    list(mu=0.00000E+00, tau.m=1.00000E-01, b0=0.00000E+00, b1=1.00000E+00, x=c(    NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA, 0.00000E+00, 0.00000E+00,     NA,     NA, 0.00000E+00,     NA, 0.00000E+00,     NA,     NA,     NA,     NA,     NA,     NA, 0.00000E+00))
</pre>
                  <p>
                  </p>
                 </div>
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                <!-- .reply -->
                <div class="bbp-reply-header" id="post-340274">
                 <div class="bbp-meta">
                  <span class="bbp-reply-post-date">
                   2012年12月5日 上午12:43
                  </span>
                  <span class="bbp-header">
                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/108809/">
                    knitr代码中含有中文时显示不全
                   </a>
                  </span>
                  <a class="bbp-reply-permalink" href="http://cos.name/cn/topic/108809/#post-340274">
                   3 楼
                  </a>
                  <span class="bbp-admin-links">
                  </span>
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                </div>
                <!-- #post-340274 -->
                <div class="even bbp-parent-forum-999 bbp-parent-topic-108809 bbp-reply-position-3 user-id-41773 topic-author post-340274 reply type-reply status-publish hentry">
                 <div class="bbp-reply-author">
                  <a class="bbp-author-avatar" href="http://cos.name/cn/profile/41773/" rel="nofollow" title="查看catfish的档案">
                   <img src="http://sdn.geekzu.org/avatar/05e4057d68060ece41c68f31982004eb?s=80&amp;d=monsterid&amp;r=g"/>
                  </a>
                  <br/>
                  <a class="bbp-author-name" href="http://cos.name/cn/profile/41773/" rel="nofollow" title="查看catfish的档案">
                   catfish
                  </a>
                  <br/>
                  <div class="bbp-author-role">
                   普通会员
                  </div>
                 </div>
                 <!-- .bbp-reply-author -->
                 <div class="bbp-reply-content">
                  <p>
                   回复 第2楼 的 谢益辉：恩，我一直怀疑是不是我语言环境没有设置对，后来想想都已经能够显示中文了，再看看knit转出来的tex，发现这里面就没有显示完全。不过我又看到网上有人做出来的文档就没有问题，但一直也没有搜到相关的解决方法。这次OK了~~谢谢~~
                  </p>
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                <!-- .reply -->
                <div class="bbp-reply-header" id="post-322718">
                 <div class="bbp-meta">
                  <span class="bbp-reply-post-date">
                   2011年9月4日 上午4:23
                  </span>
                  <span class="bbp-header">
                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/105083/">
                    对正态分布的一点疑惑
                   </a>
                  </span>
                  <a class="bbp-reply-permalink" href="http://cos.name/cn/topic/105083/#post-322718">
                   8 楼
                  </a>
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                   catfish
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                  <p>
                   回复 第4楼 的 oliyiyi：很多时候直接就对不可能取到负值的数据进行正态性检验了，然后当做正态分布处理了。
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                <div class="bbp-reply-header" id="post-322717">
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                   2011年9月4日 上午4:22
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/105083/">
                    对正态分布的一点疑惑
                   </a>
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                  <a class="bbp-reply-permalink" href="http://cos.name/cn/topic/105083/#post-322717">
                   7 楼
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                  <p>
                   回复 第5楼 的 jiao_taishan：呵呵，中心在不在原点都改变不了其定义域为（-∞，+∞）。
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                   2011年9月3日 上午8:41
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/105081/">
                    多目标最优化问题
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                   4 楼
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                   回复 第3楼 的 fenger：都可以的，mco包采用NSGA-Ⅱ算法求解多目标优化的pareto最优解。
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                   2011年9月3日 上午8:38
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/105083/">
                    对正态分布的一点疑惑
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                   3 楼
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                   回复 第2楼 的 acode：标准化不能将一个（0，+∞）上的分布变成是（-∞，+∞）上，取对数可以，不过就失去对称性了。
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                   2011年9月3日 上午5:05
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/105079/">
                    一道看起来简单做起来令人困惑的概率问题
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                   7 楼
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                  <p>
                   回复 第6楼 的 chenyan_ss：
                   <bblatex>
                    max \{P(S=B)|w_1+w_2=w, b_1+b_2=b, w_1,w_2,b_1,b_2 \in Z^+ \}
                   </bblatex>
                   ，结果应该是
                   <bblatex>
                    b_1=1
                   </bblatex>
                   ,
                   <bblatex>
                    b_2=b-1
                   </bblatex>
                   ,
                   <bblatex>
                    w_1=0
                   </bblatex>
                   ，
                   <bblatex>
                    w_2=w
                   </bblatex>
                   。当然下标可以互换。第2楼的解法令偏导数为0，求出的只是极值点。
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